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XYO’s Plan for Q4 2023: Exploring Exciting New Features and Improved Developer Tools
October 24, 2023
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Q4 2023 is going to be big for the XYO team, as we finalize critical developer tools and unveil new concepts and features. We’re excited to share our plans with you and can’t wait to show you how these developments will revolutionize the XYO ecosystem.

Keep in mind, this is only the roadmap updates for Q4–2023. The full 2024 roadmap will also be shared in the next few weeks!

Be sure to check out the updated visual Q4 roadmap on the XYO Website!

But before we venture forth, let’s talk about what’s not on the docket for Q4. As you may have guessed, if you’re familiar with our original 2023 roadmap, some of our most exciting and ambitious plans for 2023 have been bumped to Q1 and Q2 of 2024. This includes our Crypto Cards CCG and the new version of XYO World.

Wait! Hold your groans, we’re not here to disappoint you today.

There’s a simple reason for this. Those new products have got to be good, and we’re not going to release them until we’re confident they are. So we’re dedicating Q4 to improving the foundations upon which these products — and indeed the entire XYO ecosystem — are built. Moreover, many of the features queued for Q4 are key features or requirements for our products in 2024. Not only will we be improving the underlying technology, we’ll also be taking critical steps towards making future products a reality.

Part of this plan includes some really cool stuff we haven’t talked about before. You’re going to like it, we can pretty much guarantee it. But we’ll get to that in a moment — read on.

Our most important goal for wrapping up 2023 is to create a stronger foundation for both XYO World (XYOW) and Crypto Cards CCG, not to mention the wider XYO ecosystem. To achieve this, we’ve decided to move the launch of both of these products to the first half of 2024, and first focus on building core XYO Platform technology required to develop XYO dApps like these including two new XYO features — PermaShare and Live Sharing.

These new concepts are key features for both XYOW and Crypto Cards CCG, and we can’t wait to show you how they’ll enhance the user experience for players like you.

PermaShare is an XYO Tool that allows you to share a permanent snapshot of a webpage. See a funny typo on CNN’s homepage? Want to share the breaking news article in The New York Times? With PermaShare, you can truly create a permanent snapshot of anything you want to share, and it can never be changed or deleted.

This may sound similar to projects like the Internet Archive’s Wayback Machine. But PermaShare is a critical evolution of the concept. For example, the Wayback Machine doesn’t store images, and as a result, a lot of material is lost. PermaShare, on the other hand, provides a true, image-based or cryptographic data snapshot.

In contrast, here’s the earliest Wayback Machine snapshot of Whitehouse.gov, from 1996:

Moreover, PermaShare permanently validates the data saved with blockchain cryptography, providing a source and proving that snapshots taken are unaltered. This is the critical provenance the internet needs in the age of digital misinformation and AI.

PermaShare is a core feature we’ve had planned for XYO World and Crypto Cards all year. In order to share and verify important information from either of those products, we’ll include PermaShare. For example, the outcome of a game of CryptoCards can be verified by anyone with access to the PermaShare snapshot for that battle.

We’ve decided to release PermaShare as not just a mutual feature of XYO World and Crypto Cards, but as a product unto itself, because its vast array of potential uses demand that it be made easily available to both users and developers. It’s a fantastic on-ramp, a great reason to include XYO into a third party project or product, and it will doubtlessly be included in more XYO products in the future.

We’re also building out our feature called Live Sharing. This won’t be a product on its own, but it will be an important feature of XYO products moving forward and will be included in XYO’s public SDKs.

It’s already been debuted in Foreventory, and is now in the process of being refined and expanded.

This is a little different from the sharing features with which you may be familiar. The data shared is dynamic, and will update when anything changes. For example, in Foreventory, if Descartes begins getting more value out of Netflix than Nietzsche in the future, that will be reflected in the results if anyone visits the shared link.

Live Sharing is, simply put, a better way to share mutable data. If you want to share your Crypto Cards score over time, the same share link will always show your most recent statistics. (This synergizes perfectly with PermaShare, which would allow you to share your Live Sharing link at a specific moment in time, proving how much progress you’ve made.)

Together with COIN, Crypto Cards CCG and XYO World will become the second and third pillars of XYO’s new decentralized gaming ecosystem, which will harness a massive, decentralized network of users and devices to both generate and utilize astonishingly powerful aggregate data.

But there’s something else we haven’t told you about yet. Something for which we’re building the foundations. In Q1 2024, we’re introducing the XYO Builder Bounty Program.

Get ready for our first ever opportunity for fans to supercharge the power of XYO, coming in 2024. We’re giving true enthusiasts like you the chance to directly contribute to building XYO and earn exclusive, specialty rewards. Don’t miss out on the electrifying updates in our upcoming 2024 Roadmap. Stay tuned, it’s dropping soon!

In service of these goals, our future goals, as well as the wider adoption of XYO, we’re also hard at work revitalizing our developer tools. These tools have been designed to make it easy for developers to build and integrate XYO technology into their own apps and projects. We believe that improving these tools will help us reach a wider audience of developers and enthusiasts who are excited about the possibilities afforded by XYO technology.

                 

This includes updates to our Explore and Node sites to better reflect the latest developments and improvements in our technology. These tools have become integral parts of the XYO ecosystem, and we recognize the importance of keeping them current and relevant to our users. By updating these web apps, we hope to provide users with an even better experience and make it easier than ever for developers to keep XYO up-to-date in their software projects.

We’ve also previously mentioned that there are major, ongoing changes to the XYO SDKs. These changes will augment the same products that PermaShare and Live Sharing have been built to support. By including these features in our public SDKs, we ensure that XYO is as useful as possible for third party developers, and we enable all XYO products to include our best features quickly and efficiently.

Also being updated is the crucial and oft-discussed XYO protocol — the set of rules and standards upon which XYO operates. Small, specific changes across all of these developer tools include:

  • Distributed Indexing
  • Unilateral Module Manifest Support
  • Node Diagram and Module Reflection

The updates to these tools will allow both internal and external developers to build on XYO more efficiently, faster, and with greater ease than ever before.

Q4 2023 is shaping up to be an exciting time for the XYO team and our users. While we’ve decided not to rush the fun stuff we’d originally planned, we think it’s better to make sure those things are excellent when we do release them next year. And what we’re doing now will not only make those products better, but allow for the incorporation of some of their important features into other software — both internal and third party that could greatly benefit from them.

From improved developer tools and SDKs, to PermaShare and Live Sharing, we’re building the foundations for fun and exciting new consumer products and pushing the boundaries of what’s possible in the world of web3. We’re excited to continue sharing our progress and developments with you, and can’t wait to see how these new advancements will revolutionize the industry.

And, perhaps most exciting of all, we’re introducing a way for you, the people who love XYO, to help XYO succeed and get rewarded for doing it. We are beyond thrilled to finally get to tell you about the XYO Builder Bounty Program for the very first time and we can hardly wait to tell you more in future updates.

XYO posts every day to X, Facebook, and Instagram. You’ll find our latest updates on your favorite:

Ready to join the XYO community? Jump into DiscordReddit, or Telegram!

And don’t miss the news from the man, himself, Arie Trouw, CEO of XY Labs! When a really big development hits, he’ll usually be the first to tell the community, so be sure to follow him on X.

Thank you for joining us on this journey. We deeply appreciate those of you who support us, share us with your friends and family, and make up the incredible XYO community!

🚀 Click Here To Join Team Dinarian In Geomining The XYO Tokens 🚀

 

 

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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

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Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

🏛️ 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙️ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

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AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

Source

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